Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms.

Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.

Gene Essentiality Profiling Reveals Gene Networks and Synthetic Lethal Interactions with Oncogenic Ras.

The genetic dependencies of human cancers widely vary. Here, we catalog this heterogeneity and use it to identify functional gene interactions and genotype-dependent liabilities in cancer. By using genome-wide CRISPR-based screens, we generate a gene essentiality dataset across 14 human acute myeloid leukemia (AML) cell lines. Sets of genes with correlated patterns of essentiality across the lines reveal new gene relationships, the essential substrates of enzymes, and the molecular functions of uncharacterized proteins. Comparisons of differentially essential genes between Ras-dependent and -independent lines uncover synthetic lethal partners of oncogenic Ras. Screens in both human AML and engineered mouse pro-B cells converge on a surprisingly small number of genes in the Ras processing and MAPK pathways and pinpoint PREX1 as an AML-specific activator of MAPK signaling. Our findings suggest general strategies for defining mammalian gene networks and synthetic lethal interactions by exploiting the natural genetic and epigenetic diversity of human cancer cells.

Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq.

In multicellular organisms, dedicated regulatory circuits control cell type diversity and responses. The crosstalk and redundancies within these circuits and substantial cellular heterogeneity pose a major research challenge. Here, we present CRISP-seq, an integrated method for massively parallel single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-pooled screens. We show that profiling the genomic perturbation and transcriptome in the same cell enables us to simultaneously elucidate the function of multiple factors and their interactions. We applied CRISP-seq to probe regulatory circuits of innate immunity. By sampling tens of thousands of perturbed cells in vitro and in mice, we identified interactions and redundancies between developmental and signaling-dependent factors. These include opposing effects of Cebpb and Irf8 in regulating the monocyte/macrophage versus dendritic cell lineages and differential functions for Rela and Stat1/2 in monocyte versus dendritic cell responses to pathogens. This study establishes CRISP-seq as a broadly applicable, comprehensive, and unbiased approach for elucidating mammalian regulatory circuits.

Pioneer Transcription Factors Initiating Gene Network Changes.

Pioneer transcription factors have the intrinsic biochemical ability to scan partial DNA sequence motifs that are exposed on the surface of a nucleosome and thus access silent genes that are inaccessible to other transcription factors. Pioneer factors subsequently enable other transcription factors, nucleosome remodeling complexes, and histone modifiers to engage chromatin, thereby initiating the formation of an activating or repressive regulatory sequence. Thus, pioneer factors endow the competence for fate changes in embryonic development, are essential for cellular reprogramming, and rewire gene networks in cancer cells. Recent studies with reconstituted nucleosomes in vitro and chromatin binding in vivo reveal that pioneer factors can directly perturb nucleosome structure and chromatin accessibility in different ways. This review focuses on our current understanding of the mechanisms by which pioneer factors initiate gene network changes and will ultimately contribute to our ability to control cell fates at will.

Small RNAs, Large Networks: Posttranscriptional Regulons in Gram-Negative Bacteria.

Small regulatory RNA (sRNAs) are key mediators of posttranscriptional gene control in bacteria. Assisted by RNA-binding proteins, a single sRNA often modulates the expression of dozens of genes, and thus sRNAs frequently adopt central roles in regulatory networks. Posttranscriptional regulation by sRNAs comes with several unique features that cannot be achieved by transcriptional regulators. However, for optimal network performance, transcriptional and posttranscriptional control mechanisms typically go hand-in-hand. This view is reflected by the ever-growing class of mixed network motifs involving sRNAs and transcription factors, which are ubiquitous in biology and whose regulatory properties we are beginning to understand. In addition, sRNA activity can be antagonized by base-pairing with sponge RNAs, adding yet another layer of complexity to these networks. In this article, we summarize the regulatory concepts underlying sRNA-mediated gene control in bacteria and discuss how sRNAs shape the output of a network, focusing on several key examples.

A multistep computational approach reveals a neuro-mesenchymal cell population in the embryonic hematopoietic stem cell niche.

The first hematopoietic stem and progenitor cells (HSPCs) emerge in the Aorta-Gonad-Mesonephros (AGM) region of the mid-gestation mouse embryo. However, the precise nature of their supportive mesenchymal microenvironment remains largely unexplored. Here, we profiled transcriptomes of laser micro-dissected aortic tissues at three developmental stages and individual AGM cells. Computational analyses allowed the identification of several cell subpopulations within the E11.5 AGM mesenchyme, with the presence of a yet unidentified subpopulation characterized by the dual expression of genes implicated in adhesive or neuronal functions. We confirmed the identity of this cell subset as a neuro-mesenchymal population, through morphological and lineage tracing assays. Loss of function in the zebrafish confirmed that Decorin, a characteristic extracellular matrix component of the neuro-mesenchyme, is essential for HSPC development. We further demonstrated that this cell population is not merely derived from the neural crest, and hence, is a bona fide novel subpopulation of the AGM mesenchyme.

A Journey Through Genetics to Biology.

Although my engagement with human genetics emerged gradually, and sometimes serendipitously, it has held me spellbound for decades. Without my teachers, students, postdocs, colleagues, and collaborators, I would not be writing this review of my scientific adventures. Early gene and disease mapping was a satisfying puzzle-solving exercise, but building biological insight was my main goal. The project trajectory was hugely influenced by the evolutionarily conserved nature of the implicated genes and by the pace of progress in genetic technologies. The rich detail of clinical observations, particularly in eye disease, makes humans an excellent model, especially when complemented by the use of multiple other animal species for experimental validation. The contributions of collaborators and rivals also influenced our approach. We are very fortunate to work in this era of unprecedented progress in genetics and genomics.

Regeneration among animals: An evolutionary hypothesis related to aquatic versus terrestrial environment.

The present hypothesis tries to explain animal regeneration in relation to the life cycles and environment of different animals. Regeneration is a basic phenomenon present since the origin of life in the sea, as testimonial in lower or more complex extant marine animals. Aquatic animals that evolved an indirect development, forming larvae and transiting into the adult stage through metamorphosis, use gene networks present in their genome for these transformations. In case of injury or organ loss as adults, they can re-utilize most or part of the gene networks previously activated during larval growth and metamorphosis. In contrast, terrestrial animals that evolved life cycles with the elimination of larvae and metamorphosis for the adaptation to land conditions lost some of the genes implicated in these post-developmental processes and consequently also the ability to regenerate. Few arthropods and lizards are capable to form hydrated regenerative blastemas with a similar consistence of embryonic tissues. The present hypothesis submits that regeneration cannot be activated in the dry land environment and consequently was largely or completely abolished in terrestrial animals. After injury or organ loss, nematodes, most arthropods and terrestrial vertebrates can only form scars or a limited healing or regengrow in juveniles. This is a process where somatic growth is superimposed to wound healing so that the apparent regeneration derives from the combination from both processes. When full growth is terminated these terrestrial animals can only heal by scarring.

Comparative and integrative single cell analysis reveals new insights into the transcriptional immaturity of stem cell-derived ß cells.

Diabetes cell replacement therapy has the potential to be transformed by human pluripotent stem cell-derived ß cells (SC-ß cells). However, the precise identity of SC-ß cells in relationship to primary fetal and adult ß-cells remains unclear. Here, we used single-cell sequencing datasets to characterize the transcriptional identity of islets from in vitro differentiation, fetal islets, and adult islets. Our analysis revealed that SC-ß cells share a core ß-cell transcriptional identity with human adult and fetal ß-cells, however SC-ß cells possess a unique transcriptional profile characterized by the persistent expression and activation of progenitor and neural-biased gene networks. These networks are present in SC-ß cells, irrespective of the derivation protocol used. Notably, fetal ß-cells also exhibit this neural signature at the transcriptional level. Our findings offer insights into the transcriptional identity of SC-ß cells and underscore the need for further investigation of the role of neural transcriptional networks in their development.

Ovarian cancer classification and prognosis assessment model based on prognostic target genes in key microRNA-target gene networks.

BACKGROUND: The present study was designed to screen key microRNA (miRNA)-target gene networks for ovarian cancer (OC) and to classify and construct a risk assessment system for OC based on the target genes. METHODS: OC sample data of The Cancer Genome Atlas dataset and GSE26193, GSE30161, GSE63885 and GSE9891 datasets were retrospectively collected. Pearson correlation analysis and targeted analysis of miRNA and target gene were performed to screen key miRNA-target gene networks. Target genes associated with the prognosis of OC were screened from key miRNA-target gene networks for consensus clustering and least absolute shrinkage and selection operator-based regression machine learning analysis of OC samples. RESULTS: Twenty target genes of 2651 key miRNA-target gene pairs had significant prognostic correlation in each OC cohort, and OC was divided into three clusters. There were differences in prognostic outcome, biological pathways, immune cell abundance and susceptibility to immune checkpoint blockade (ICB) therapy and anti-tumor drugs among the three molecular clusters. S2 exhibited the least advantage in prognosis and immunotherapy response rate in the three molecular clusters, and the pathways regulating immunity, hypoxia, metabolism and promoting malignant progression of cancer, as well as infiltrating immune and stromal cell population abundance, were the highest in this cluster. An eight-target gene prognostic model was created, and the risk index obtained by using this model not only significantly distinguished the immune characteristics of the sample, but also predicted the response of the sample to ICB treatment, and helped to screen 36 potential anti-OC drugs. CONCLUSIONS: The present study provides a classification strategy for OC based on prognostic target genes in key miRNA-target gene networks, and creates a risk assessment system for predicting prognosis and response to ICB therapy in OC patients, providing molecular basis for prognosis and precise treatment of OC.

A developmental lineage-based gene co-expression network for mouse pancreatic ß-cells reveals a role for Zfp800 in pancreas development.

To gain a deeper understanding of pancreatic ß-cell development, we used iterative weighted gene correlation network analysis to calculate a gene co-expression network (GCN) from 11 temporally and genetically defined murine cell populations. The GCN, which contained 91 distinct modules, was then used to gain three new biological insights. First, we found that the clustered protocadherin genes are differentially expressed during pancreas development. Pcdhγ genes are preferentially expressed in pancreatic endoderm, Pcdhß genes in nascent islets, and Pcdhα genes in mature ß-cells. Second, after extracting sub-networks of transcriptional regulators for each developmental stage, we identified 81 zinc finger protein (ZFP) genes that are preferentially expressed during endocrine specification and ß-cell maturation. Third, we used the GCN to select three ZFPs for further analysis by CRISPR mutagenesis of mice. Zfp800 null mice exhibited early postnatal lethality, and at E18.5 their pancreata exhibited a reduced number of pancreatic endocrine cells, alterations in exocrine cell morphology, and marked changes in expression of genes involved in protein translation, hormone secretion and developmental pathways in the pancreas. Together, our results suggest that developmentally oriented GCNs have utility for gaining new insights into gene regulation during organogenesis.

Water deficit response in nodulated soybean roots: a comprehensive transcriptome and translatome network analysis.

BACKGROUND: Soybean establishes a mutualistic interaction with nitrogen-fixing rhizobacteria, acquiring most of its nitrogen requirements through symbiotic nitrogen fixation. This crop is susceptible to water deficit; evidence suggests that its nodulation status-whether it is nodulated or not-can influence how it responds to water deficit. The translational control step of gene expression has proven relevant in plants subjected to water deficit. RESULTS: Here, we analyzed soybean roots' differential responses to water deficit at transcriptional, translational, and mixed (transcriptional + translational) levels. Thus, the transcriptome and translatome of four combined-treated soybean roots were analyzed. We found hormone metabolism-related genes among the differentially expressed genes (DEGs) at the translatome level in nodulated and water-restricted plants. Also, weighted gene co-expression network analysis followed by differential expression analysis identified gene modules associated with nodulation and water deficit conditions. Protein-protein interaction network analysis was performed for subsets of mixed DEGs of the modules associated with the plant responses to nodulation, water deficit, or their combination. CONCLUSIONS: Our research reveals that the stand-out processes and pathways in the before-mentioned plant responses partially differ; terms related to glutathione metabolism and hormone signal transduction (2 C protein phosphatases) were associated with the response to water deficit, terms related to transmembrane transport, response to abscisic acid, pigment metabolic process were associated with the response to nodulation plus water deficit. Still, two processes were common: galactose metabolism and branched-chain amino acid catabolism. A comprehensive analysis of these processes could lead to identifying new sources of tolerance to drought in soybean.

Hybridization and gene expression: Beyond differentially expressed genes.

Gene expression has a key role in reproductive isolation, and studies of hybrid gene expression have identified mechanisms causing hybrid sterility. Here, we review the evidence for altered gene expression following hybridization and outline the mechanisms shown to contribute to altered gene expression in hybrids. Transgressive gene expression, transcending that of both parental species, is pervasive in early generation sterile hybrids, but also frequently observed in viable, fertile hybrids. We highlight studies showing that hybridization can result in transgressive gene expression, also in established hybrid lineages or species. Such extreme patterns of gene expression in stabilized hybrid taxa suggest that altered hybrid gene expression may result in hybridization-derived evolutionary novelty. We also conclude that while patterns of misexpression in hybrids are well documented, the understanding of the mechanisms causing misexpression is lagging. We argue that jointly assessing differences in cell composition and cell-specific changes in gene expression in hybrids, in addition to assessing changes in chromatin and methylation, will significantly advance our understanding of the basis of altered gene expression. Moreover, uncovering to what extent evolution of gene expression results in altered expression for individual genes, or entire networks of genes, will advance our understanding of how selection moulds gene expression. Finally, we argue that jointly studying the dual roles of altered hybrid gene expression, serving both as a mechanism for reproductive isolation and as a substrate for hybrid ecological adaptation, will lead to significant advances in our understanding of the evolution of gene expression.

Cuticle Development And The Underlying Transcriptome-Metabolome Associations During Early Seedling Establishment.

The plant cuticle is a complex extracellular lipid barrier that has multiple protective functions. We investigated cuticle deposition by integrating metabolomics and transcriptomics data gathered from six different maize seedling organs of four genotypes, the inbred lines B73 and Mo17, and their reciprocal hybrids. These datasets captured the developmental transition of the seedling from heterotrophic skotomorphogenic growth to autotrophic photomorphogenic growth, which is a transition that is highly vulnerable to environmental stresses. Statistical interrogation of these data reveals that the predominant determinant of cuticle composition is seedling organ type, whereas the seedling genotype has a smaller effect on this phenotype. Gene-to-metabolite associations assessed by integrated statistical analyses identified three gene networks connected with the deposition of different elements of the cuticle: a) cuticular waxes; b) monomers of lipidized cell wall biopolymers, including cutin and suberin; and c) both of these elements. These gene networks reveal three metabolic programs that appear to support cuticle deposition, including processes of chloroplast biogenesis, lipid metabolism, and molecular regulation (e.g., transcription factors, post-translational regulators and phytohormones). This study demonstrates the wider physiological metabolic context that can determine cuticle deposition and lays the groundwork for new targets for modulating properties of this protective barrier.

Spatial biology of Ising-like synthetic genetic networks.

BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS: Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS: Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.

Resequencing of Brazilian locally adapted cattle breeds revealed variants in candidate genes and transcription factors for meat fatty acid profile.

The beef cattle industry has experienced a shift driven by a market demand for healthier meat, cost efficiency and environmental sustainability in recent years. Consequently, there has been a growing focus on the fatty acids content and functions of meat in cattle breeding programmes. Besides, a deeper understanding of the biological mechanisms influencing the expression of different phenotypes related to fatty acid profiles is crucial. In this study, we aimed to identify Single-Nucleotide Variants (SNV) and Insertion/Deletion (InDels) DNA variants in candidate genes related to fatty acid profiles described in genomic, transcriptomic and proteomic studies conducted in beef cattle breeds. Utilizing whole-genome re-sequencing data from Brazilian locally adapted bovine breeds, namely Caracu and Pantaneiro, we identified SNVs and InDels associated with 23,947 genes. From these, we identified 318 candidate genes related to fatty acid profiles that contain variants. Subsequently, we select only genes with SNVs and InDels in their promoter, 5' UTR and coding region. Through the gene-biological process network, approximately 19 genes were highlighted. Furthermore, considering the studied trait and a literature review, we selected the main transcription factors (TF). Functional analysis via gene-TF network allowed us to identify the 30 most likely candidate genes for meat fatty acid profile in cattle. LIPE, MFSD2A and SREBF1 genes were highlighted in networks due to their biological importance. Further dissection of these genes revealed 15 new variants found in promoter regions of Caracu and Pantaneiro sequences. The gene networks facilitated a better functional understanding of genes and TF, enabling the identification of variants potentially related to the expression of candidate genes for meat fatty acid profiles in cattle.

Analysis of the Gene Networks and Pathways Correlated with Tissue Differentiation in Prostate Cancer.

Prostate cancer (PCa) is the most prevalent non-cutaneous cancer in men. Early PCa detection has been made possible by the adoption of screening methods based on the serum prostate-specific antigen and Gleason score (GS). The aim of this study was to correlate gene expression with the differentiation level of prostate adenocarcinomas, as indicated by GS. We used data from The Cancer Genome Atlas (TCGA) and included 497 prostate cancer patients, 52 of which also had normal tissue sample sequencing data. Gene ontology analysis revealed that higher GSs were associated with greater responses to DNA damage, telomere lengthening, and cell division. Positive correlation was found with transcription factor activator of the adenovirus gene E2 (E2F) and avian myelocytomatosis viral homolog (MYC) targets, G2M checkpoints, DNA repair, and mitotic spindles. Immune cell deconvolution revealed high M0 macrophage counts and an increase in M2 macrophages dependent on the GS. The molecular pathways most correlated with GSs were cell cycle, RNA transport, and calcium signaling (depleted). A combinatorial approach identified a set of eight genes able to differentiate by k-Nearest Neighbors (kNN) between normal tissues, low-Gleason tissues, and high-Gleason tissues with high accuracy. In conclusion, our study could be a step forward to better understanding the link between gene expression and PCa progression and aggressiveness.

Transcriptional regulation of tomato fruit ripening.

An intrinsic and genetically determined ripening program of tomato fruits often depends upon the appropriate activation of tissue- and stage-specific transcription factors in space and time. The past two decades have yielded considerable progress in detailing these complex transcriptional as well as hormonal regulatory circuits paramount to fleshy fruit ripening. This non-linear ripening process is strongly controlled by the MADS-box and NOR family of proteins, triggering a transcriptional response associated with the progression of fruit ripening. Deepening insights into the connection between MADS-RIN and plant hormones related transcription factors, such as ERFs and ARFs, further conjugates the idea that several signaling units work in parallel to define an output fruit ripening transcriptome. Besides these TFs, the role of other families of transcription factors such as MYB, GLK, WRKY, GRAS and bHLH have also emerged as important ripening regulators. Other regulators such as EIN and EIL proteins also determine the transcriptional landscape of ripening fruits. Despite the abundant knowledge of the complex spectrum of ripening networks in the scientific domain, identifying more ripening effectors would pave the way for a better understanding of fleshy fruit ripening at the molecular level. This review provides an update on the transcriptional regulators of tomato fruit ripening.

A multimodal deep learning model to infer cell-type-specific functional gene networks.

BACKGROUND: Functional gene networks (FGNs) capture functional relationships among genes that vary across tissues and cell types. Construction of cell-type-specific FGNs enables the understanding of cell-type-specific functional gene relationships and insights into genetic mechanisms of human diseases in disease-relevant cell types. However, most existing FGNs were developed without consideration of specific cell types within tissues. RESULTS: In this study, we created a multimodal deep learning model (MDLCN) to predict cell-type-specific FGNs in the human brain by integrating single-nuclei gene expression data with global protein interaction networks. We systematically evaluated the prediction performance of the MDLCN and showed its superior performance compared to two baseline models (boosting tree and convolutional neural network). Based on the predicted cell-type-specific FGNs, we observed that cell-type marker genes had a higher level of hubness than non-marker genes in their corresponding cell type. Furthermore, we showed that risk genes underlying autism and Alzheimer's disease were more strongly connected in disease-relevant cell types, supporting the cellular context of predicted cell-type-specific FGNs. CONCLUSIONS: Our study proposes a powerful deep learning approach (MDLCN) to predict FGNs underlying a diverse set of cell types in human brain. The MDLCN model enhances prediction accuracy of cell-type-specific FGNs compared to single modality convolutional neural network (CNN) and boosting tree models, as shown by higher areas under both receiver operating characteristic (ROC) and precision-recall curves for different levels of independent test datasets. The predicted FGNs also show evidence for the cellular context and distinct topological features (i.e. higher hubness and topological score) of cell-type marker genes. Moreover, we observed stronger modularity among disease-associated risk genes in FGNs of disease-relevant cell types. For example, the strength of connectivity among autism risk genes was stronger in neurons, but risk genes underlying Alzheimer's disease were more connected in microglia.

Beyond conflict: Kinship theory of intragenomic conflict predicts individual variation in altruistic behaviour.

Behavioural variation is essential for animals to adapt to different social and environmental conditions. The Kinship Theory of Intragenomic Conflict (KTIC) predicts that parent-specific alleles can support different behavioural strategies to maximize allele fitness. Previous studies, including in honey bees (Apis mellifera), supported predictions of the KTIC for parent-specific alleles to promote selfish behaviour. Here, we test the KTIC prediction that for altruism-promoting genes (i.e. those that promote behaviours that support the reproductive fitness of kin), the allele with the higher altruism optimum should be selected to be expressed while the other is silenced. In honey bee colonies, workers act altruistically when tending to the queen by performing a 'retinue' behaviour, distributing the queen's mandibular pheromone (QMP) throughout the hive. Workers exposed to QMP do not activate their ovaries, ensuring they care for the queen's brood instead of competing to lay unfertilized eggs. Due to the haplodiploid genetics of honey bees, the KTIC predicts that response to QMP is favoured by the maternal genome. We report evidence for parent-of-origin effects on the retinue response behaviour, ovarian development and gene expression in brains of worker honey bees exposed to QMP, consistent with the KTIC. Additionally, we show enrichment for genes with parent-of-origin expression bias within gene regulatory networks associated with variation in bees' response to QMP. Our study demonstrates that intragenomic conflict can shape diverse social behaviours and influence expression patterns of single genes as well as gene networks.